A novel optimal coordinated control strategy for the updated robot system for single port surgery

Robotics Computer Surgery

Song

Zhang

et al. 2018

Background: Open surgical consoles widely employed in minimally invasive surgery have better ergonomics than closed consoles. To enhance surgical robots' ergonomics, operational efficiency, and safety, an effective master-slave motion alignment model should be established.Methods: The kinematic model of the robot system based on laparoscopic camera coordinate system is built in the first place. Then, the relative pose between the operator's eyes and the display is measured by Tobii Eye Tracking Sensor and is subsequently used to improve the master-slave motion alignment model. Results: Robot threading experiments are conducted by two doctors and three testers to verify the kinematic model. As a result, in contrast to the original model, the improved model reduces both operation time and the number of collisions.Conclusions: The improved master-slave motion alignment model, in which the transformation matrix between the operator's eyes and the display is employed, raises the ergonomics, operational efficiency, and safety.

Section: Methodsmentioning

confidence: 99%

Master‐slave motion alignment for an open surgical console

Robotics Computer Surgery

Song

Zhang

et al. 2018

“…Moreover, they also require miniaturized and highly integrated mechanical structure, high dexterity for tissue manipulation with sufficient triangulation and manoeuvrability in a small crowded in-vivo workspace, and controlled through teleoperation schemes. Nevertheless, the dense installation of miniaturised robotic arms and instruments may easily raise safety and efficiency issues, including self-interference and collision in the limited workspace, especially when performing coordinated manipulation [27], [28]. Besides being more compact with smaller size and higher dexterity, dual-arms are usually arranged for SPS robot with more constraints as they need to restore operational triangulation after parallelly going through the small incision [29].…”

Section: Introductionmentioning

confidence: 99%

Anthropomorphic Dual-Arm Coordinated Control for a Single-Port Surgical Robot Based on Dual-Step Optimization

Bai

IEEE Trans. Med. Robot. Bionics

Cao

et al. 2022

Self Cite

Effective teleoperation of the small-scale and highlyintegrated robots for single-port surgery (SPS) imposes unique control and human-robot interaction challenges. Traditional isometric teleoperation schemes mainly focus on end-to-end trajectory mapping, which is problematic when applied to SPS robotic control, especially for dual-arm coordinated operation. Inspired by the human arm configuration in boxing maneuvers, an optimized anthropomorphic coordinated control strategy based on a dual-step optimization approach is proposed. Theoretical derivation and solvability of the problem are addressed, and the effectiveness of the method is further demonstrated in detailed simulation and in-vitro experiments. The proposed control strategy has been shown to perform dexterous SPS bimanual manipulation more effectively, involving less instrument-interference and is free from singularities, thereby improving the safety and efficiency of SPS operations.

“…T ELEOPERATION provides surgeons with the ability to operate on the patient side remotely, where the human intention can be transferred through communication channels [1]- [4]. Teleoperation mechanism isolates surgeons from the patient's neighbouring, which fulfills the medical requirements for diagnosis and treatment of infectious diseases [5] and surgical operations [6].…”

Section: Introductionmentioning

confidence: 99%

Deep Reinforcement Learning-Based Control Framework for Multilateral Telesurgery

Bacha

Bai

IEEE Trans. Med. Robot. Bionics

et al. 2022

Self Cite

The upper boundary of time delay is often required in traditional telesurgery control design, which would result in infeasibility of telesurgery across regions. To overcome this issue, this paper introduces a new control framework based on deep deterministic policy gradient (DDPG) reinforcement learning (RL) algorithm. The developed framework effectively overcomes the phase difference and data loss caused by time delays, which facilitates the restoration of surgeon's intention and interactive force. Kalman filter (KF) is employed to blend multiple surgeons' commands and predict the final local commands, respectively. The control framework ensures synchronization tracking performance and transparency. Prior knowledge of time delay is therefore not required. Simulation and experiment results have demonstrated the merits of the proposed framework.